BLACK'S EXPLANATION OF NOISE VS INFORMATION

If you are a student of finance, you must have surely heard or seen the infamous Black- Scholes option pricing model. For those who do not about the model, it is basically an equation or a framework by which we can determine the prices of options. Options are one of the major financial derivative security. Fischer Black and Myron Scholes published the paper in 1973 thereby developing the whole derivatives industry. 

The famous Black- Scholes Option Pricing Model

The above is the formula for which Fischer Black is most well known. However, there is another paper he published in 1986 in the Journal of Finance titled "NOISE". This paper I believe is very much relevant in today's Finance and Economics industry. Actually, if you think about it, it goes beyond just Finance and Economics and can be traced back to every major discipline or event that happens in our world on daily basis. So, let's start by reviewing what Black thinks about NOISE.

The reality of the world: Noise Vs Information/ Signal

Black starts the paper by emphasizing the role that noise plays in our daily life. He specifically talks about three fields: Financial markets, Econometric models, and Macroeconomic Policies. The financial market is full of noise. From multi-national media outlets to internet blogs like this one, there might or might not be information carried from one node to another (speaking in networking terms). However, one has to understand the fact that noise in financial markets is actually a pre-requisite for liquidity. This means it is the noise that tempts people in trading financial assets thereby creating a liquid market and hence helping create or at least trying to create an efficient market. I said "trying to" create because, on the other hand, it is also one of those major components that actually make the market inefficient. Noise trading, as defined by Black, is basically trading on noise as if it were information. 

I want you to do an experiment. Just open up CNBC or Bloomberg news and just watch it for a while, what you shall start hearing is that some cause and effect relationship apparently occurred and that's why the concerned event happened. Essentially, what media outlets are out there is to just SELL. In this case, they are selling the narratives. These narratives are created to actually satisfy people's behavioral bias. For example, there might be news that the stock market crashed because the US sanctioned Iran. Now, this may or may not be true but the narrative has already been prepared and they are ready to sell this to the general population. And that's how the entire media business runs. What this causes is not that the people suddenly change their opinions or decisions after seeing/ hearing the news, but rather this news will be on their head for a while and it will only need some reinforcement from other outlets such as peer group or family members regardless of whether the news was noise or information before the people will start doubting their initial beliefs. The herd mentality sure does kick in.  

Another great distinction that Black makes in the paper is the idea of information traders and noise traders. Information traders make their trade decisions based on an information edge. They know something that very few know in the market. This can be generated by anything from insider information (although illegal) to an excellent research team. Furthermore, it is very likely that those other few who know about the superior information are themselves information traders. On the other spectrum, we have a group called noise traders. These are the majority of people who you see trading in the markets. They trade on their beliefs that some security might go up or down. In the words of Black (1986), noise trading is trading on noise as if it were information. A word of caution has to be declared here that information trading gives traders an edge, however, it by no means guarantees a profit. And to top it off, the information traders can never be sure that their trading is based strictly on information rather than noise. In nutshell, when you see prices of financial securities in the market, remember that those prices have some combination of noise and information embedded in it. 

Finally, he goes on to discuss how due to noise, even the market pricing anomalies like betting on low-priced stock which has been empirically proved to generate premium returns in the long run, can have a significant period of underperformance. For example, imagine a bunch of noise traders found out about these pricing anomalies like low b/m or small caps which are publicly available information which further means this information is already in the price. So, in the hopes of generating above-average returns, they start trading on it and when a large number of the so-called noise traders trade these low multiple stocks, they make the markets for these securities less efficeíent. What this does is that it widens the gap between the price and the intrinsic value of those stocks. Hence, the price will just be a noisy proxy of the value. Similarly, the fundamental entities like earning or book value that people use in price multiples also will be a noisy estimate when it reaches the market. In other words, it might be the case that the discrepancy between price and value would take many years to finally come to equilibrium.

So, in this article, we saw how noise is both an important factor for market efficiency and also a factor that prevents us from making consistent profits. By no means I wanted to present you with a gloom and doom scenario and proposing a utopian world where nothing is in order and we should be skeptical about everything. My objective with this article was rather to just highlight a point and put an emphasis on something that we have to be wary about while creating our pricing models and managing a portfolio.